2019 Long Term Internship - Quantitative Research - Electronic Trading

BNP PARIBAS · Competitive · London (central)
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BNP Paribas Global Markets provides cross-asset investment, hedging, financing, research and market intelligence to corporate and institutional clients, as well as private and retail banking networks.

Global Markets' sustainable, long term business model seamlessly connects clients to capital markets throughout 38 markets in EMEA, Asia Pacific and the Americas, with innovative solutions and digital platforms.

Through Global Markets, clients can access a full universe of opportunities in equity derivatives, foreign exchange and local markets, commodity derivatives, rates, primary and credit markets and prime solutions and financing.

We have open long term intern positions in our e-FIC team.

The e-FIC Team carries out quantitative research in electronic trading of Fixed Income and Currency (FX) products. Its aim is to provide fully automated solutions for market making.

Eligibility Criteria

  • A minimum of a Masters or PhD in a quantitative subject such as Computer Science, Mathematics, Physics, Quantitative Finance or Engineering
  • Excellent programming skills (C++, Python, Java, R or other equivalent)
  • Interest in financial markets, economics and quantitative finance
  • Experience of electronic markets, models and arbitrage strategies (advantage)
  • Delivery-driven mindset
  • Strong interpersonal skills and proactive approach to problem solving
  • Data manipulation and database experience
  • Ability to work under pressure and multi-task
  • Strong organisational skills
  • Team Player

Roles and Responsibilities

  • Development of algorithmic pricing, quoting, risk management and execution tools to automate BNPP’s FIC market making activities
  • Conduct research and analysis using historical datasets to develop models behind the automation tools
  • Interact with Trading, Sales and IT to ensure a timely delivery of projects to all interested parties' standards
  • Continuously improve existing models to adapt to an ever changing market landscape

Apply to position

Deadline: 30 June 2019
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